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def get_paragraph ( self ) : self . text = '' for x in range ( randint ( 5 , 12 ) ) : sentence = self . _write_sentence ( ) self . text = self . text + sentence return self . text
Write a paragraph of 5 sentences .
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def skip_job ( counter ) : try : host_number = int ( socket . gethostname ( ) . split ( '-' ) [ - 1 ] ) except ValueError : return False if ( counter + host_number - ( NUMBER_OF_HOSTS - 1 ) ) % NUMBER_OF_HOSTS == 0 : return False return True
Should we skip the job based on its number
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def generate_crontab ( current_crontab , path_to_jobs , path_to_app , unique_id ) : set_disable_envar = '' if os . environ . get ( 'DISABLE_COLLECTORS' ) == 'true' : set_disable_envar = 'DISABLE_COLLECTORS={} ' . format ( os . environ . get ( 'DISABLE_COLLECTORS' ) ) job_template = '{schedule} ' '{set_disable_envar}' '...
Returns a crontab with jobs from job path
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def map_parameters ( cls , params ) : d = { } for k , v in six . iteritems ( params ) : d [ cls . FIELD_MAP . get ( k . lower ( ) , k ) ] = v return d
Maps parameters to form field names
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def world_to_image ( bbox , size ) : px_per_unit = ( float ( size [ 0 ] ) / bbox . width , float ( size [ 1 ] ) / bbox . height ) return lambda x , y : ( ( x - bbox . xmin ) * px_per_unit [ 0 ] , size [ 1 ] - ( y - bbox . ymin ) * px_per_unit [ 1 ] )
Function generator to create functions for converting from world coordinates to image coordinates
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def warp ( self , target_bbox , target_size = None ) : # Determine target size based on pixels per unit of the source image and the target bounding box reprojected # to the source projection. if not target_size : px_per_unit = ( float ( self . image . size [ 0 ] ) / self . bbox . width , float ( self . image . size [ 1...
Returns a copy of this image warped to a target size and bounding box
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def try_get_department ( department_or_code ) : try : value = take_first_department_code ( department_or_code ) except AssertionError : value = department_or_code if value in DEPARTMENT_MAPPING : value = DEPARTMENT_MAPPING [ value ] return value
Try to take the first department code or fall back to string as passed
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def debug ( self ) : url = '{}debug/status' . format ( self . url ) try : return make_request ( url , timeout = self . timeout ) except ServerError as err : return { "error" : str ( err ) }
Retrieve the debug information from the identity manager .
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def login ( self , username , json_document ) : url = '{}u/{}' . format ( self . url , username ) make_request ( url , method = 'PUT' , body = json_document , timeout = self . timeout )
Send user identity information to the identity manager .
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def discharge ( self , username , macaroon ) : caveats = macaroon . third_party_caveats ( ) if len ( caveats ) != 1 : raise InvalidMacaroon ( 'Invalid number of third party caveats (1 != {})' '' . format ( len ( caveats ) ) ) url = '{}discharger/discharge?discharge-for-user={}&id={}' . format ( self . url , quote ( use...
Discharge the macarooon for the identity .
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def discharge_token ( self , username ) : url = '{}discharge-token-for-user?username={}' . format ( self . url , quote ( username ) ) logging . debug ( 'Sending identity info to {}' . format ( url ) ) response = make_request ( url , method = 'GET' , timeout = self . timeout ) try : macaroon = response [ 'DischargeToken...
Discharge token for a user .
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def set_extra_info ( self , username , extra_info ) : url = self . _get_extra_info_url ( username ) make_request ( url , method = 'PUT' , body = extra_info , timeout = self . timeout )
Set extra info for the given user .
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def get_extra_info ( self , username ) : url = self . _get_extra_info_url ( username ) return make_request ( url , timeout = self . timeout )
Get extra info for the given user .
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def is_complete ( self ) : return all ( p . name in self . values for p in self . parameters if p . required )
Do all required parameters have values?
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def _encode_write ( dynamizer , data , action , key ) : # Strip null values out of data data = dict ( ( ( k , dynamizer . encode ( v ) ) for k , v in six . iteritems ( data ) if not is_null ( v ) ) ) return { action : { key : data , } }
Encode an item write command
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def encode_query_kwargs ( dynamizer , kwargs ) : ret = { } for k , v in six . iteritems ( kwargs ) : if '__' not in k : raise TypeError ( "Invalid query argument '%s'" % k ) name , condition_key = k . split ( '__' ) # Convert ==None to IS_NULL if condition_key == 'eq' and is_null ( v ) : condition_key = 'null' v = True...
Encode query constraints in Dynamo format
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def attrs ( self , dynamizer ) : ret = { self . key : { 'Action' : self . action , } } if not is_null ( self . value ) : ret [ self . key ] [ 'Value' ] = dynamizer . encode ( self . value ) return ret
Get the attributes for the update
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def expected ( self , dynamizer ) : if self . _expect_kwargs : return encode_query_kwargs ( dynamizer , self . _expect_kwargs ) if self . _expected is not NO_ARG : ret = { } if is_null ( self . _expected ) : ret [ 'Exists' ] = False else : ret [ 'Value' ] = dynamizer . encode ( self . _expected ) ret [ 'Exists' ] = Tru...
Get the expected values for the update
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def flush ( self ) : items = [ ] for data in self . _to_put : items . append ( encode_put ( self . connection . dynamizer , data ) ) for data in self . _to_delete : items . append ( encode_delete ( self . connection . dynamizer , data ) ) self . _write ( items ) self . _to_put = [ ] self . _to_delete = [ ]
Flush pending items to Dynamo
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def _write ( self , items ) : response = self . _batch_write_item ( items ) if 'consumed_capacity' in response : # Comes back as a list from BatchWriteItem self . consumed_capacity = sum ( response [ 'consumed_capacity' ] , self . consumed_capacity ) if response . get ( 'UnprocessedItems' ) : unprocessed = response [ '...
Perform a batch write and handle the response
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def resend_unprocessed ( self ) : LOG . info ( "Re-sending %d unprocessed items." , len ( self . _unprocessed ) ) while self . _unprocessed : to_resend = self . _unprocessed [ : MAX_WRITE_BATCH ] self . _unprocessed = self . _unprocessed [ MAX_WRITE_BATCH : ] LOG . info ( "Sending %d items" , len ( to_resend ) ) self ....
Resend all unprocessed items
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def _batch_write_item ( self , items ) : kwargs = { 'RequestItems' : { self . tablename : items , } , 'ReturnConsumedCapacity' : self . return_capacity , 'ReturnItemCollectionMetrics' : self . return_item_collection_metrics , } return self . connection . call ( 'batch_write_item' , * * kwargs )
Make a BatchWriteItem call to Dynamo
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def _get_path ( entity_id ) : try : path = entity_id . path ( ) except AttributeError : path = entity_id if path . startswith ( 'cs:' ) : path = path [ 3 : ] return path
Get the entity_id as a string if it is a Reference .
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def _get ( self , url ) : try : response = requests . get ( url , verify = self . verify , cookies = self . cookies , timeout = self . timeout , auth = self . _client . auth ( ) ) response . raise_for_status ( ) return response except HTTPError as exc : if exc . response . status_code in ( 404 , 407 ) : raise EntityNot...
Make a get request against the charmstore .
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def _meta ( self , entity_id , includes , channel = None ) : queries = [ ] if includes is not None : queries . extend ( [ ( 'include' , include ) for include in includes ] ) if channel is not None : queries . append ( ( 'channel' , channel ) ) if len ( queries ) : url = '{}/{}/meta/any?{}' . format ( self . url , _get_...
Retrieve metadata about an entity in the charmstore .
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def entities ( self , entity_ids ) : url = '%s/meta/any?include=id&' % self . url for entity_id in entity_ids : url += 'id=%s&' % _get_path ( entity_id ) # Remove the trailing '&' from the URL. url = url [ : - 1 ] data = self . _get ( url ) return data . json ( )
Get the default data for entities .
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def bundle ( self , bundle_id , channel = None ) : return self . entity ( bundle_id , get_files = True , channel = channel )
Get the default data for a bundle .
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def charm ( self , charm_id , channel = None ) : return self . entity ( charm_id , get_files = True , channel = channel )
Get the default data for a charm .
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def charm_icon_url ( self , charm_id , channel = None ) : url = '{}/{}/icon.svg' . format ( self . url , _get_path ( charm_id ) ) return _add_channel ( url , channel )
Generate the path to the icon for charms .
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def charm_icon ( self , charm_id , channel = None ) : url = self . charm_icon_url ( charm_id , channel = channel ) response = self . _get ( url ) return response . content
Get the charm icon .
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def bundle_visualization ( self , bundle_id , channel = None ) : url = self . bundle_visualization_url ( bundle_id , channel = channel ) response = self . _get ( url ) return response . content
Get the bundle visualization .
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def bundle_visualization_url ( self , bundle_id , channel = None ) : url = '{}/{}/diagram.svg' . format ( self . url , _get_path ( bundle_id ) ) return _add_channel ( url , channel )
Generate the path to the visualization for bundles .
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def entity_readme_url ( self , entity_id , channel = None ) : url = '{}/{}/readme' . format ( self . url , _get_path ( entity_id ) ) return _add_channel ( url , channel )
Generate the url path for the readme of an entity .
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def entity_readme_content ( self , entity_id , channel = None ) : readme_url = self . entity_readme_url ( entity_id , channel = channel ) response = self . _get ( readme_url ) return response . text
Get the readme for an entity .
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def archive_url ( self , entity_id , channel = None ) : url = '{}/{}/archive' . format ( self . url , _get_path ( entity_id ) ) return _add_channel ( url , channel )
Generate a URL for the archive of an entity ..
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def file_url ( self , entity_id , filename , channel = None ) : url = '{}/{}/archive/{}' . format ( self . url , _get_path ( entity_id ) , filename ) return _add_channel ( url , channel )
Generate a URL for a file in an archive without requesting it .
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def files ( self , entity_id , manifest = None , filename = None , read_file = False , channel = None ) : if manifest is None : manifest_url = '{}/{}/meta/manifest' . format ( self . url , _get_path ( entity_id ) ) manifest_url = _add_channel ( manifest_url , channel ) manifest = self . _get ( manifest_url ) manifest =...
Get the files or file contents of a file for an entity .
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def resource_url ( self , entity_id , name , revision ) : return '{}/{}/resource/{}/{}' . format ( self . url , _get_path ( entity_id ) , name , revision )
Return the resource url for a given resource on an entity .
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def config ( self , charm_id , channel = None ) : url = '{}/{}/meta/charm-config' . format ( self . url , _get_path ( charm_id ) ) data = self . _get ( _add_channel ( url , channel ) ) return data . json ( )
Get the config data for a charm .
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def entityId ( self , partial , channel = None ) : url = '{}/{}/meta/any' . format ( self . url , _get_path ( partial ) ) data = self . _get ( _add_channel ( url , channel ) ) return data . json ( ) [ 'Id' ]
Get an entity s full id provided a partial one .
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def search ( self , text , includes = None , doc_type = None , limit = None , autocomplete = False , promulgated_only = False , tags = None , sort = None , owner = None , series = None ) : queries = self . _common_query_parameters ( doc_type , includes , owner , promulgated_only , series , sort ) if len ( text ) : quer...
Search for entities in the charmstore .
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def list ( self , includes = None , doc_type = None , promulgated_only = False , sort = None , owner = None , series = None ) : queries = self . _common_query_parameters ( doc_type , includes , owner , promulgated_only , series , sort ) if len ( queries ) : url = '{}/list?{}' . format ( self . url , urlencode ( queries...
List entities in the charmstore .
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def _common_query_parameters ( self , doc_type , includes , owner , promulgated_only , series , sort ) : queries = [ ] if includes is not None : queries . extend ( [ ( 'include' , include ) for include in includes ] ) if doc_type is not None : queries . append ( ( 'type' , doc_type ) ) if promulgated_only : queries . a...
Extract common query parameters between search and list into slice .
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def fetch_related ( self , ids ) : if not ids : return [ ] meta = '&id=' . join ( id [ 'Id' ] for id in ids ) url = ( '{url}/meta/any?id={meta}' '&include=bundle-metadata&include=stats' '&include=supported-series&include=extra-info' '&include=bundle-unit-count&include=owner' ) . format ( url = self . url , meta = meta ...
Fetch related entity information .
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def fetch_interfaces ( self , interface , way ) : if not interface : return [ ] if way == 'requires' : request = '&requires=' + interface else : request = '&provides=' + interface url = ( self . url + '/search?' + 'include=charm-metadata&include=stats&include=supported-series' '&include=extra-info&include=bundle-unit-c...
Get the list of charms that provides or requires this interface .
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def debug ( self ) : url = '{}/debug/status' . format ( self . url ) data = self . _get ( url ) return data . json ( )
Retrieve the debug information from the charmstore .
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def query_server ( self , outfile , age , metallicity ) : params = copy . deepcopy ( self . download_defaults ) epsilon = 1e-4 lage = np . log10 ( age * 1e9 ) lage_min , lage_max = params [ 'isoc_lage0' ] , params [ 'isoc_lage1' ] if not ( lage_min - epsilon < lage < lage_max + epsilon ) : msg = 'Age outside of valid r...
Server query for the isochrone file .
535
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def run ( self , coords = None , debug = False ) : #self.grid.precompute() self . grid . search ( coords = coords ) return self . grid
Run the likelihood grid search
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def write ( self , outfile ) : data = odict ( ) data [ 'PIXEL' ] = self . roi . pixels_target # Full data output (too large for survey) if self . config [ 'scan' ] [ 'full_pdf' ] : data [ 'LOG_LIKELIHOOD' ] = self . log_likelihood_sparse_array . T data [ 'RICHNESS' ] = self . richness_sparse_array . T data [ 'RICHNESS_...
Save the likelihood results as a sparse HEALPix map .
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def from_uri ( cls , uri , socket_timeout = None , auto_decode = False ) : parts = six . moves . urllib . parse . urlparse ( uri ) if parts . scheme . lower ( ) not in ( 'beanstalk' , 'beanstalkd' ) : raise ValueError ( 'Invalid scheme %s' % parts . scheme ) ipv6_md = re . match ( r'^\[([0-9a-fA-F:]+)\](:[0-9]+)?$' , p...
Construct a synchronous Beanstalk Client from a URI .
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def list_tubes ( self ) : with self . _sock_ctx ( ) as sock : self . _send_message ( 'list-tubes' , sock ) body = self . _receive_data_with_prefix ( b'OK' , sock ) tubes = yaml_load ( body ) return tubes
Return a list of tubes that this beanstalk instance knows about
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def stats ( self ) : with self . _sock_ctx ( ) as socket : self . _send_message ( 'stats' , socket ) body = self . _receive_data_with_prefix ( b'OK' , socket ) stats = yaml_load ( body ) return stats
Return a dictionary with a bunch of instance - wide statistics
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def put_job ( self , data , pri = 65536 , delay = 0 , ttr = 120 ) : with self . _sock_ctx ( ) as socket : message = 'put {pri} {delay} {ttr} {datalen}\r\n' . format ( pri = pri , delay = delay , ttr = ttr , datalen = len ( data ) , data = data ) . encode ( 'utf-8' ) if not isinstance ( data , bytes ) : data = data . en...
Insert a new job into whatever queue is currently USEd
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def watchlist ( self , tubes ) : tubes = set ( tubes ) for tube in tubes - self . _watchlist : self . watch ( tube ) for tube in self . _watchlist - tubes : self . ignore ( tube )
Set the watchlist to the given tubes
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def watch ( self , tube ) : with self . _sock_ctx ( ) as socket : self . desired_watchlist . add ( tube ) if tube not in self . _watchlist : self . _send_message ( 'watch {0}' . format ( tube ) , socket ) self . _receive_id ( socket ) self . _watchlist . add ( tube ) if self . initial_watch : if tube != 'default' : sel...
Add the given tube to the watchlist .
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def ignore ( self , tube ) : with self . _sock_ctx ( ) as socket : if tube not in self . _watchlist : raise KeyError ( tube ) if tube != 'default' : self . desired_watchlist . remove ( tube ) if tube in self . _watchlist : self . _send_message ( 'ignore {0}' . format ( tube ) , socket ) self . _receive_id ( socket ) se...
Remove the given tube from the watchlist .
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def stats_job ( self , job_id ) : with self . _sock_ctx ( ) as socket : if hasattr ( job_id , 'job_id' ) : job_id = job_id . job_id self . _send_message ( 'stats-job {0}' . format ( job_id ) , socket ) body = self . _receive_data_with_prefix ( b'OK' , socket ) job_status = yaml_load ( body ) return job_status
Fetch statistics about a single job
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def stats_tube ( self , tube_name ) : with self . _sock_ctx ( ) as socket : self . _send_message ( 'stats-tube {0}' . format ( tube_name ) , socket ) body = self . _receive_data_with_prefix ( b'OK' , socket ) return yaml_load ( body )
Fetch statistics about a single tube
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def reserve_job ( self , timeout = 5 ) : timeout = int ( timeout ) if self . socket_timeout is not None : if timeout >= self . socket_timeout : raise ValueError ( 'reserve_job timeout must be < socket timeout' ) if not self . _watchlist : raise ValueError ( 'Select a tube or two before reserving a job' ) with self . _s...
Reserve a job for this connection . Blocks for TIMEOUT secionds and raises TIMED_OUT if no job was available
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def delete_job ( self , job_id ) : if hasattr ( job_id , 'job_id' ) : job_id = job_id . job_id with self . _sock_ctx ( ) as socket : self . _send_message ( 'delete {0}' . format ( job_id ) , socket ) self . _receive_word ( socket , b'DELETED' )
Delete the given job id . The job must have been previously reserved by this connection
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def bury_job ( self , job_id , pri = 65536 ) : if hasattr ( job_id , 'job_id' ) : job_id = job_id . job_id with self . _sock_ctx ( ) as socket : self . _send_message ( 'bury {0} {1}' . format ( job_id , pri ) , socket ) return self . _receive_word ( socket , b'BURIED' )
Mark the given job_id as buried . The job must have been previously reserved by this connection
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def kick_job ( self , job_id ) : if hasattr ( job_id , 'job_id' ) : job_id = job_id . job_id with self . _sock_ctx ( ) as socket : self . _send_message ( 'kick-job {0}' . format ( job_id ) , socket ) self . _receive_word ( socket , b'KICKED' )
Kick the given job id . The job must either be in the DELAYED or BURIED state and will be immediately moved to the READY state .
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def use ( self , tube ) : with self . _sock_ctx ( ) as socket : if self . current_tube != tube : self . desired_tube = tube self . _send_message ( 'use {0}' . format ( tube ) , socket ) self . _receive_name ( socket ) self . current_tube = tube
Start producing jobs into the given tube .
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def using ( self , tube ) : try : current_tube = self . current_tube self . use ( tube ) yield BeanstalkInsertingProxy ( self , tube ) finally : self . use ( current_tube )
Context - manager to insert jobs into a specific tube
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def kick_jobs ( self , num_jobs ) : with self . _sock_ctx ( ) as socket : self . _send_message ( 'kick {0}' . format ( num_jobs ) , socket ) return self . _receive_id ( socket )
Kick some number of jobs from the buried queue onto the ready queue .
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def pause_tube ( self , tube , delay = 3600 ) : with self . _sock_ctx ( ) as socket : delay = int ( delay ) self . _send_message ( 'pause-tube {0} {1}' . format ( tube , delay ) , socket ) return self . _receive_word ( socket , b'PAUSED' )
Pause a tube for some number of seconds preventing it from issuing jobs .
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def interval ( best , lo = np . nan , hi = np . nan ) : return [ float ( best ) , [ float ( lo ) , float ( hi ) ] ]
Pythonized interval for easy output to yaml
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def peak_interval ( data , alpha = _alpha , npoints = _npoints ) : peak = kde_peak ( data , npoints ) x = np . sort ( data . flat ) n = len ( x ) # The number of entries in the interval window = int ( np . rint ( ( 1.0 - alpha ) * n ) ) # The start, stop, and width of all possible intervals starts = x [ : n - window ] ...
Identify interval using Gaussian kernel density estimator .
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def supplement ( self , coordsys = 'gal' ) : from ugali . utils . projector import gal2cel , gal2cel_angle from ugali . utils . projector import cel2gal , cel2gal_angle coordsys = coordsys . lower ( ) kwargs = dict ( usemask = False , asrecarray = True ) out = copy . deepcopy ( self ) if ( 'lon' in out . names ) and ( ...
Add some supplemental columns
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def median ( self , name , * * kwargs ) : data = self . get ( name , * * kwargs ) return np . percentile ( data , [ 50 ] )
Median of the distribution .
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def kde_peak ( self , name , npoints = _npoints , * * kwargs ) : data = self . get ( name , * * kwargs ) return kde_peak ( data , npoints )
Calculate peak of kernel density estimator
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def kde ( self , name , npoints = _npoints , * * kwargs ) : data = self . get ( name , * * kwargs ) return kde ( data , npoints )
Calculate kernel density estimator for parameter
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def peak_interval ( self , name , alpha = _alpha , npoints = _npoints , * * kwargs ) : data = self . get ( name , * * kwargs ) return peak_interval ( data , alpha , npoints )
Calculate peak interval for parameter .
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def min_interval ( self , name , alpha = _alpha , * * kwargs ) : data = self . get ( name , * * kwargs ) return min_interval ( data , alpha )
Calculate minimum interval for parameter .
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def results ( self , names = None , alpha = _alpha , mode = 'peak' , * * kwargs ) : if names is None : names = self . names ret = odict ( ) for n in names : ret [ n ] = getattr ( self , '%s_interval' % mode ) ( n , * * kwargs ) return ret
Calculate the results for a set of parameters .
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def densify ( self , factor = 10 ) : x = [ ] y = [ ] for ii in range ( 0 , len ( self . x ) - 2 ) : p = Parabola ( self . x [ ii : ii + 3 ] , self . y [ ii : ii + 3 ] ) x . append ( np . linspace ( self . x [ ii ] , self . x [ ii + 1 ] , factor ) [ 0 : - 1 ] ) y . append ( p ( x [ - 1 ] ) ) p = Parabola ( self . x [ le...
Increase the density of points along the parabolic curve .
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def profileUpperLimit ( self , delta = 2.71 ) : a = self . p_2 b = self . p_1 if self . vertex_x < 0 : c = self . p_0 + delta else : c = self . p_0 - self . vertex_y + delta if b ** 2 - 4. * a * c < 0. : print ( 'WARNING' ) print ( a , b , c ) return 0. return max ( ( np . sqrt ( b ** 2 - 4. * a * c ) - b ) / ( 2. * a ...
Compute one - sided upperlimit via profile method .
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def bayesianUpperLimit ( self , alpha , steps = 1.e5 , plot = False ) : x_dense , y_dense = self . densify ( ) y_dense -= np . max ( y_dense ) # Numeric stability f = scipy . interpolate . interp1d ( x_dense , y_dense , kind = 'linear' ) x = np . linspace ( 0. , np . max ( x_dense ) , steps ) pdf = np . exp ( f ( x ) /...
Compute one - sided upper limit using Bayesian Method of Helene . Several methods of increasing numerical stability have been implemented .
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def bayesianUpperLimit2 ( self , alpha , steps = 1.e5 , plot = False ) : cut = ( ( self . y / 2. ) > - 30. ) # Numeric stability try : f = scipy . interpolate . interp1d ( self . x [ cut ] , self . y [ cut ] , kind = 'cubic' ) except : f = scipy . interpolate . interp1d ( self . x [ cut ] , self . y [ cut ] , kind = 'l...
Compute one - sided upper limit using Bayesian Method of Helene .
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def confidenceInterval ( self , alpha = 0.6827 , steps = 1.e5 , plot = False ) : x_dense , y_dense = self . densify ( ) y_dense -= np . max ( y_dense ) # Numeric stability f = scipy . interpolate . interp1d ( x_dense , y_dense , kind = 'linear' ) x = np . linspace ( 0. , np . max ( x_dense ) , steps ) # ADW: Why does t...
Compute two - sided confidence interval by taking x - values corresponding to the largest PDF - values first .
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def hms2dec ( hms ) : DEGREE = 360. HOUR = 24. MINUTE = 60. SECOND = 3600. if isstring ( hms ) : hour , minute , second = np . array ( re . split ( '[hms]' , hms ) ) [ : 3 ] . astype ( float ) else : hour , minute , second = hms . T decimal = ( hour + minute * 1. / MINUTE + second * 1. / SECOND ) * ( DEGREE / HOUR ) re...
Convert longitude from hours minutes seconds in string or 3 - array format to decimal degrees .
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def dms2dec ( dms ) : DEGREE = 360. HOUR = 24. MINUTE = 60. SECOND = 3600. # Be careful here, degree needs to be a float so that negative zero # can have its signbit set: # http://docs.scipy.org/doc/numpy-1.7.0/reference/c-api.coremath.html#NPY_NZERO if isstring ( dms ) : degree , minute , second = np . array ( re . sp...
Convert latitude from degrees minutes seconds in string or 3 - array format to decimal degrees .
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def getArgumentParser ( self , configManager , config ) : argParser = argparse . ArgumentParser ( self . description ) for configName , configDict in configManager . configs . items ( ) : cmdName = configName . replace ( "_" , "-" ) argParser . add_argument ( '--%s' % cmdName , default = None , help = configDict [ 'des...
May be overidden to provide custom functionality . Constructs an argparse . ArgumentParser used to parse configuration options from the command line .
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def parse ( self , configManager , config ) : argParser = self . getArgumentParser ( configManager , config ) return vars ( argParser . parse_args ( ) )
Parses commandline arguments given a series of configuration options .
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def candidates ( text ) : for Pmatch in finditer ( TARGET , text ) : # the punctuation mark itself P = Pmatch . group ( 1 ) # is it a boundary? B = bool ( match ( NEWLINE , Pmatch . group ( 5 ) ) ) # L & R start = Pmatch . start ( ) end = Pmatch . end ( ) Lmatch = search ( LTOKEN , text [ max ( 0 , start - BUFSIZE ) : ...
Given a text string get candidates and context for feature extraction and classification
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def extract_one ( self , L , P , R ) : yield "*bias*" # L feature(s) if match ( QUOTE , L ) : L = QUOTE_TOKEN elif isnumberlike ( L ) : L = NUMBER_TOKEN else : yield "len(L)={}" . format ( min ( len ( L ) , CLIP ) ) if "." in L : yield "L:*period*" if not self . nocase : cf = case_feature ( R ) if cf : yield "L:{}'" . ...
Given left context L punctuation mark P and right context R extract features . Probability distributions for any quantile - based features will not be modified .
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def fit ( self , text , epochs = EPOCHS ) : logger . debug ( "Extracting features and classifications." ) Phi = [ ] Y = [ ] for ( L , P , R , gold , _ ) in Detector . candidates ( text ) : Phi . append ( self . extract_one ( L , P , R ) ) Y . append ( gold ) self . classifier . fit ( Y , Phi , epochs ) logger . debug (...
Given a string text use it to train the segmentation classifier for epochs iterations .
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def predict ( self , L , P , R ) : phi = self . extract_one ( L , P , R ) return self . classifier . predict ( phi )
Given an left context L punctuation mark P and right context R return True iff this observation is hypothesized to be a sentence boundary .
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def segments ( self , text ) : start = 0 for ( L , P , R , B , end ) in Detector . candidates ( text ) : # if there's already a newline there, we have nothing to do if B : continue if self . predict ( L , P , R ) : yield text [ start : end ] . rstrip ( ) start = end # otherwise, there's probably not a sentence boundary...
Given a string of text return a generator yielding each hypothesized sentence string
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def evaluate ( self , text ) : cx = BinaryConfusion ( ) for ( L , P , R , gold , _ ) in Detector . candidates ( text ) : guess = self . predict ( L , P , R ) cx . update ( gold , guess ) if not gold and guess : logger . debug ( "False pos.: L='{}', R='{}'." . format ( L , R ) ) elif gold and not guess : logger . debug ...
Given a string of text compute confusion matrix for the classification task .
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def scale ( mask , mag_scale , outfile = None ) : msg = "'mask.scale': ADW 2018-05-05" DeprecationWarning ( msg ) mask_new = hp . UNSEEN * np . ones ( len ( mask ) ) mask_new [ mask == 0. ] = 0. mask_new [ mask > 0. ] = mask [ mask > 0. ] + mag_scale if outfile is not None : pix = np . nonzero ( mask_new > 0. ) [ 0 ] d...
Scale the completeness depth of a mask such that mag_new = mag + mag_scale . Input is a full HEALPix map . Optionally write out the scaled mask as an sparse HEALPix map .
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def mask_roi_unique ( self ) : # There is no good inherent way in numpy to do this... # http://stackoverflow.com/q/16970982/ # Also possible and simple: #return np.unique(zip(self.mask_1.mask_roi_sparse,self.mask_2.mask_roi_sparse)) A = np . vstack ( [ self . mask_1 . mask_roi_sparse , self . mask_2 . mask_roi_sparse ]...
Assemble a set of unique magnitude tuples for the ROI
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def mask_roi_digi ( self ) : # http://stackoverflow.com/q/24205045/#24206440 A = np . vstack ( [ self . mask_1 . mask_roi_sparse , self . mask_2 . mask_roi_sparse ] ) . T B = self . mask_roi_unique AA = np . ascontiguousarray ( A ) BB = np . ascontiguousarray ( B ) dt = np . dtype ( ( np . void , AA . dtype . itemsize ...
Get the index of the unique magnitude tuple for each pixel in the ROI .
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def _fracRoiSparse ( self ) : self . frac_roi_sparse = np . min ( [ self . mask_1 . frac_roi_sparse , self . mask_2 . frac_roi_sparse ] , axis = 0 ) return self . frac_roi_sparse
Calculate an approximate pixel coverage fraction from the two masks .
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def _pruneMMD ( self , minimum_solid_angle ) : logger . info ( 'Pruning mask based on minimum solid angle of %.2f deg^2' % ( minimum_solid_angle ) ) solid_angle_mmd = self . solid_angle_mmd * ( self . solid_angle_mmd > minimum_solid_angle ) if solid_angle_mmd . sum ( ) == 0 : msg = "Pruned mask contains no solid angle....
Remove regions of magnitude - magnitude space where the unmasked solid angle is statistically insufficient to estimate the background .
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def _pruneCMD ( self , minimum_solid_angle ) : logger . info ( 'Pruning mask based on minimum solid angle of %.2f deg^2' % ( minimum_solid_angle ) ) self . solid_angle_cmd *= self . solid_angle_cmd > minimum_solid_angle if self . solid_angle_cmd . sum ( ) == 0 : msg = "Pruned mask contains no solid angle." logger . err...
Remove regions of color - magnitude space where the unmasked solid angle is statistically insufficient to estimate the background .
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def plot ( self ) : msg = "'%s.plot': ADW 2018-05-05" % self . __class__ . __name__ DeprecationWarning ( msg ) import ugali . utils . plotting mask = hp . UNSEEN * np . ones ( hp . nside2npix ( self . nside ) ) mask [ self . roi . pixels ] = self . mask_roi_sparse mask [ mask == 0. ] = hp . UNSEEN ugali . utils . plott...
Plot the magnitude depth .
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def build_expected ( dynamizer , expected ) : ret = { } for k , v in six . iteritems ( expected ) : if is_null ( v ) : ret [ k ] = { 'Exists' : False , } else : ret [ k ] = { 'Exists' : True , 'Value' : dynamizer . encode ( v ) , } return ret
Build the Expected parameters from a dict
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def build_expression_values ( dynamizer , expr_values , kwargs ) : if expr_values : values = expr_values return dynamizer . encode_keys ( values ) elif kwargs : values = dict ( ( ( ':' + k , v ) for k , v in six . iteritems ( kwargs ) ) ) return dynamizer . encode_keys ( values )
Build ExpresionAttributeValues from a value or kwargs
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def connect_to_host ( cls , host = 'localhost' , port = 8000 , is_secure = False , session = None , access_key = None , secret_key = None , * * kwargs ) : warnings . warn ( "connect_to_host is deprecated and will be removed. " "Use connect instead." ) if session is None : session = botocore . session . get_session ( ) ...
Connect to a specific host .
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